Summary of the Key Points
This article discusses how, in the era of AI (where AI assistants/agents become new entities in transactions), a new set of “payment + service” infrastructure is needed—equivalent to an AI version of a “POS machine.” The team led by former Tencent executive Wu Xin has targeted China’s over 100 million small businesses that have not yet been digitized, such as those selling goods in Yiwu, community water delivery services, and private fitness coaches. They use AI technology to help these businesses become more integrated into the digital landscape. This isn’t just about writing code; it’s about solving the entire process from identifying customer needs to delivering the services. The goal is to make these businesses accessible to AI assistants, just as QR codes enabled digitalization for merchants during the mobile payment era. Ultimately, this system aims to transform these scattered businesses into a supply network that can be directly utilized by AI assistants, creating new business opportunities.
1. What exactly is the “POS machine” in the AI era? And why is it more important than QR codes?
You can think of an AI assistant as an intelligent butler that can help you with tasks like ordering breakfast, booking massages, or finding water delivery services. To do this, the assistant needs to know where these services are available and understand the relevant information (such as prices, availability, and service details) in a format that AI can process directly.
Similar to QR codes in mobile payment, they don’t just serve as payment methods; they also help digitize other aspects of business operations. For example, in the case of water delivery services, QR codes allow users to manage the number of buckets delivered or access information about the quality of essential oils used by therapists. The “POS machine” in the AI era does more than just providing an interface for AI; it helps businesses digitize their entire operations. Without this system, even if an AI assistant wants to help with a purchase, it wouldn’t know where to find the necessary services.
2. Why focus on small businesses rather than large clients?
In 2024, Wu Xin’s team tried targeting large clients with a project that sold for 500,000 yuan, generating a 40% profit margin. While this was profitable, it required a large number of sales, delivery, and project management staff, which is a labor-intensive approach. Large clients (such as supermarkets and chain brands) already have their own IT teams that can adapt to new technologies on their own. The real need lies with the 120 million small businesses in China; only about 20 million of them are currently using e-commerce platforms, while the remaining 100 million (including community water delivery services, private coaches, and small vendors in Yiwu) have genuine digitalization needs but face high costs associated with traditional software development. With AI Coding, these small businesses can now afford to digitize their operations, making them accessible to AI assistants.
3. The hardest part of serving small businesses is not the technology; it’s providing tangible results
Small businesses are different from large companies that rely on programmers. They don’t care about the specific AI models or architectures used; they just want solutions that can help them manage their operations efficiently, such as tracking customer memberships, managing inventory, and processing payments. This means that the development process must address the entire workflow, including obtaining merchant accounts, configuring payment systems, and handling refunds—all tasks that small businesses often don’t understand. It’s not enough to simply generate code; a comprehensive solution is required.
4. How do AI assistants find these businesses? Structured data is crucial
When an AI assistant looks for services, it compares the information provided by different providers. For example, when searching for “in-home massage” services, an AI would prefer a provider with clear and detailed information (such as the type of massage offered, price, availability, and delivery times) rather than a vague description. Structured data makes it easier for the assistant to process transactions quickly.
5. What will happen once this network is fully established?
If many businesses join this system, products from various regions (like goods from Yiwu, fresh flowers from Yunnan, or clothing from Guangzhou) will become accessible directly through AI assistants, forming a connected network. For instance, an AI assistant could place an order for birthday flowers, coordinate the creation of a custom card, and arrange delivery without the user having to search multiple platforms separately. This would create new business opportunities across different industries and regions, just as QR codes enabled the growth of services like food delivery and car ridesharing during the mobile payment era.
In summary, this AI “POS machine” solves the issue of connecting providers in the digital age by enabling undigitized small businesses to join the AI ecosystem, allowing them to be found by AI assistants and ultimately creating a more efficient and intelligent transaction network.